John Searle's Speech Acts (1969) and Expression and Meaning (1979) developed a highly original and influential approach to the study of language. But behind both works lay the assumption that the philosophy of language is in the end a branch of the philosophy of the mind: speech acts are forms of human action and represent just one example of the mind's capacity to relate the human organism to the world. The present book is concerned with these biologically fundamental capacities, and, (...) though third in the sequence, in effect it provides the philosophical foundations for the other two. Intentionality is taken to be the crucial mental phenomenon, and its analysis involves wide-ranging discussions of perception, action, causation, meaning, and reference. In all these areas John Searle has original and stimulating views. He ends with a resolution of the 'mind-body' problem. (shrink)

Through the use of such "folk" concepts as belief, desire, intention, and expectation, Daniel Dennett asserts in this first full scale presentation of...

Linking the process of rational decision making to emotions, an award-winning scientist who has done extensive research with brain-damaged patients notes the dependence of thought processes on feelings and the body's survival-oriented regulators. 50,000 first printing.

In this lucid portrayal of human behavior, Fred Dretske provides an original account of the way reasons function in the causal explanation of behavior.

What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

Introduction: Something on the State of the Art 1 I. Functionalism and Realism 1. Operationalism and Ordinary Language 35 2. The Appeal to Tacit Knowledge in Psychological Explanations 63 3. What Psychological States are Not 79 4. Three Cheers for Propositional Attitudes 100 II. Reduction and Unity of Science 5. Special Sciences 127 6. Computation and Reduction 146 III. Intensionality and Mental Representation 7. Propositional Attitudes 177 8. Tom Swift and His Procedural Grandmother 204 9. Methodological Solipsism Considered as a (...) Research Strategy in Cognitive Psychology 225 IV. Nativism 10. The Present Status of the Innateness Controversy 257 Notes 317. (shrink)

Intentional explanation and attributions of mentality -- International systems -- Reply to Arbib and Gunderson -- Brain writing and mind reading -- The nature of theory in psychology -- Skinner skinned -- Why the law of effect will not go away -- A cure for the common code? -- Artificial intelligence as philosophy and as psychology -- Objects of consciousness and the nature of experience -- Are dreams experiences? -- Toward a cognitive theory of consciousness -- Two approaches to mental (...) images -- Why you can't make a computer that feels pain -- Free will and personhood -- Mechanism and responsibility -- The abilities of men and machines -- Conditions of personhood -- On giving libertarians what they say they want -- How to change your mind -- Where am I? (shrink)

The publication of this book is an event in the making. All over the world scientists, psychologists, and philosophers are waiting to read Antonio Damasio's new theory of the nature of consciousness and the construction of the self. A renowned and revered scientist and clinician, Damasio has spent decades following amnesiacs down hospital corridors, waiting for comatose patients to awaken, and devising ingenious research using PET scans to piece together the great puzzle of consciousness. In his bestselling Descartes' Error, Damasio (...) revealed the critical importance of emotion in the making of reason. Building on this foundation, he now shows how consciousness is created. Consciousness is the feeling of what happens-our mind noticing the body's reaction to the world and responding to that experience. Without our bodies there can be no consciousness, which is at heart a mechanism for survival that engages body, emotion, and mind in the glorious spiral of human life. A hymn to the possibilities of human existence, a magnificent work of ingenious science, a gorgeously written book, The Feeling of What Happens is already being hailed as a classic. (shrink)

" Biosemantics " was the title of a paper on mental representation originally printed in The Journal of Philosophy in 1989. It contained a much abbreviated version of the work on mental representation in Language Thought and Other Biological Categories. There I had presented a naturalist theory of intentional signs generally, including linguistic representations, graphs, charts and diagrams, road sign symbols, animal communications, the "chemical signals" that regulate the function of glands, and so forth. But the term " biosemantics " (...) has usually been applied only to the theory of mental representation. Let me first characterize a more general class of theories called "teleological theories of mental content" of which biosemantics is an example. Then I will discuss the details that distinguish biosemantics from other naturalistic teleological theories. (shrink)

There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the symbol grounding problem : How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their shapes, be grounded (...) in anything but other meaningless symbols? The problem is analogous to trying to learn Chinese from a Chinese/Chinese dictionary alone. A candidate solution is sketched: Symbolic representations must be grounded bottom-up in nonsymbolic representations of two kinds: iconic representations, which are analogs of the proximal sensory projections of distal objects and events, and categorical representations, which are learned and innate feature-detectors that pick out the invariant features of object and event categories from their sensory projections. Elementary symbols are the names of these object and event categories, assigned on the basis of their categorical representations. Higher-order symbolic representations, grounded in these elementary symbols, consist of symbol strings describing category membership relations. Connectionism is one natural candidate for the mechanism that learns the invariant features underlying categorical representations, thereby connecting names to the proximal projections of the distal objects they stand for. In this way connectionism can be seen as a complementary component in a hybrid nonsymbolic/symbolic model of the mind, rather than a rival to purely symbolic modeling. Such a hybrid model would not have an autonomous symbolic module, however; the symbolic functions would emerge as an intrinsically dedicated symbol system as a consequence of the bottom-up grounding of categories ' names in their sensory representations. Symbol manipulation would be governed not just by the arbitrary shapes of the symbol tokens, but by the nonarbitrary shapes of the icons and category invariants in which they are grounded. (shrink)

Semantic Engines: An Introduction to Mind Design, John C. Haugeland; Computer Science as Empirical Inquiry: Symbols and Search, Alan Newell and Herbert A. Simon; Complexity and the Study of Artificial and Human Intelligence, Zenon Pylyshyn; A Framework for Representing Knowledge, Marvin Minsky; Artificial Intelligence---A Personal View, David Marr; Artificial Intelligence Meets Natural Stupidity, Drew McDermott; From Micro-Worlds to Knowledge Representation: AI at an Impasse, Hubert L. Dreyfus; Reductionism and the Nature of Psychology, Hilary Putnam; Intentional Systems, Daniel C. Dennett; The (...) Nature and Plausibility of Cognitivism, John C. Haugeland; Minds, Brains, and Programs, John R. Searle; MethodologicalSolipsism Considered as a Research Strategy in Cognitive Psychology, Jerry A. Fodor; The Material Mind, Donald Davidson. (shrink)

This anthology brings together readings mainly from contemporary philosophers, but also from writers of the past two centuries, on the philosophy of mind. Some of the main questions addressed are: is a human being really a mind in relation to a body; if so, what exactly is this mind and how it is related to the body; and are there any grounds for supposing that the mind survives the disintegration of the body?

This article focuses on the problem of representational content. Accounting for representational content is the central issue in contemporary naturalism: it is the major remaining task facing a naturalistic conception of the world. Representational content is also the central barrier to contemporary cognitive science and artificial intelligence: it is not possible to understand representation in animals nor to construct machines with genuine representation given current (lack of) understanding of what representation is. An elaborated critique is offered to current approaches to (...) representation, arguing that the basic underlying approach is, at root, logically incoherent, and, thus, that standard approaches are doomed to failure. An alternative model of representation - interactivism - is presented that avoids or solves the problems facing standard approaches. Interactivism is framed by a version of functionalism, and a naturalization of that functionalism completes an outline of a naturalization of representation and representational content. (shrink)

Searle's celebrated Chinese Room Argument has shaken the foundations of Artificial Intelligence. Many refutations have been attempted, but none seem convincing. This paper is an attempt to sort out explicitly the assumptions and the logical, methodological and empirical points of disagreement. Searle is shown to have underestimated some features of computer modeling, but the heart of the issue turns out to be an empirical question about the scope and limits of the purely symbolic (computational) model of the mind. Nonsymbolic modeling (...) turns out to be immune to the Chinese Room Argument. The issues discussed include the Total Turing Test, modularity, neural modeling, robotics, causality and the symbol-grounding problem. (shrink)

Emergence seems necessary for any naturalistic account of the world — none of our familiar world existed at the time of the Big Bang, and it does now — and normative emergence is necessary for any naturalistic account of biology and mind — mental phenomena, such as representation, learning, rationality, and so on, are normative. But Jaegwon Kim’s argument appears to render causally efficacious emergence impossible, and Hume’s argument appears to render normative emergence impossible, and, in its general form, it (...) precludes any emergence at all. I argue that both of these barriers can be overcome, and, in fact, that they each constitute reductios of their respective underlying presuppositions. In particular, causally efficacious ontological emergence can be modeled, but only within a process metaphysics, thus avoiding Kim’s argument, and by making use of non-abbreviatory forms of definition, thus avoiding Hume’s argument. I illustrate these points with models of the emergent nature of normative function and of representation. (shrink)

When certain formal symbol systems (e.g., computer programs) are implemented as dynamic physical symbol systems (e.g., when they are run on a computer) their activity can be interpreted at higher levels (e.g., binary code can be interpreted as LISP, LISP code can be interpreted as English, and English can be interpreted as a meaningful conversation). These higher levels of interpretability are called "virtual" systems. If such a virtual system is interpretable as if it had a mind, is such a "virtual (...) mind" real? This is the question addressed in this "virtual" symposium, originally conducted electronically among four cognitive scientists: Donald Perlis, a computer scientist, argues that according to the computationalist thesis, virtual minds are real and hence Searle's Chinese Room Argument fails, because if Searle memorized and executed a program that could pass the Turing Test in Chinese he would have a second, virtual, Chinese-understanding mind of which he was unaware (as in multiple personality). Stevan Harnad, a psychologist, argues that Searle's Argument is valid, virtual minds are just hermeneutic overinterpretations, and symbols must be grounded in the real world of objects, not just the virtual world of interpretations. Computer scientist Patrick Hayes argues that Searle's Argument fails, but because Searle does not really implement the program: A real implementation must not be homuncular but mindless and mechanical, like a computer. Only then can it give rise to a mind at the virtual level. Philosopher Ned Block suggests that there is no reason a mindful implementation would not be a real one. (shrink)

Wayne D. Christensen and Cliff A. Hooker.

Information and representation are thought to be intimately related. Representation, in fact, is commonly considered to be a special kind of information. It must be a _special_ kind, because otherwise all of the myriad instances of informational relationships in the universe would be representational -- some restrictions must be placed on informational relationships in order to refine the vast set into those that are truly representational. I will argue that information in this general sense is important to genuine agents, but (...) that it is a blind alley with regard to the attempt to understand representation. On the other hand, I will also argue that a different, quite non-standard, form of information is central to genuine representation. First I turn to some of the reasons why information as usually considered is the wrong category for understanding representation; second to an alternative model of representation -- one that is naturally emergent in autonomous agents, and that does involve information, but not in any standard form; and third I return to standard notions of informational relationships and show what they are in fact useful for. (shrink)

The following paper presents a characterization of three distinctions fundamental to computationalism, viz., the distinction between analog and digital machines, representation and nonrepresentation-using systems, and direct and indirect perceptual processes. Each distinction is shown to rest on nothing more than the methodological principles which justify the explanatory framework of the special sciences.

The problem of semantic content is the problem of explicating those features of brain processes by virtue of which they may properly be thought to possess meaning or reference. This paper criticizes the account of semantic content associated with fodor's version of cognitive science, And offers an alternative account based on mathematical communication theory. Its key concept is that of a neuronal representation maintaining a high-Level of mutual information with a designated external state of affairs under changing conditions of perceptual (...) presentation. (shrink)

The problem of semantic content is the problem of explicating those features of brain processes by virtue of which they may properly be thought to possess meaning or reference. This paper criticizes the account of semantic content associated with fodor's version of cognitive science, And offers an alternative account based on mathematical communication theory. Its key concept is that of a neuronal representation maintaining a high-Level of mutual information with a designated external state of affairs under changing conditions of perceptual (...) presentation. (shrink)